Neighbor-based Outlier Detection Algorithms for Julia

Wrapper for Python-based Outlier Detection Algorithms in Julia

Load and save ARFF files

Distributed High-Performance Symbolic Regression in Julia

Julia Project website

Effortless Bayesian Deep Learning through Laplace Approximation for Flux.jl neural networks.

The official registry of general Julia packages

Implements the Partitioned Least Squares algorithms

Linear models

AD-backend agnostic system defining custom forward and reverse mode rules. This is the light weight core to allow you to define rules for your functions in your packages, without depending on any p…

Parallel & lightning fast implementation of available classic and contemporary variants of the KMeans clustering algorithm

Unicode-based scientific plotting for working in the terminal

Julia wrapper of the python library CatBoost for boosted decision trees

Re-implementation of a spatially explicit (grid-based) model of NZ forest dynamics - see Morales et al. 2017 (doi: 10.1016/j.ecolmodel.2017.04.007) and Brock et al. 2020 (doi: 10.1111/1365-2745.133…

Julia implementation of the scikit-learn API https://cstjean.github.io/ScikitLearn.jl/dev/

TreeParzen.jl, a pure Julia hyperparameter optimiser with MLJ integration

Implementation of a Partial Least Squares Regressor

A data-focused namespace for packages to share functions

Boosted trees in Julia

An interface for tables in Julia

A variety of loaders for various NLP corpora.

Neural-Network Outlier Detection Algorithms for Julia

An interface to the deep learning package Flux.jl from the MLJ.jl toolbox